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Abstract
The recent Weather Surveillance Radar-1988 Doppler (WSR-88D) network upgrade to dual-polarization capabilities allows for bulk characterization of microphysical processes in northeastern U.S. winter storms for the first time. In this study, the quasi-vertical profile (QVP) technique (wherein data from a given elevation angle scan are azimuthally averaged and the range coordinate is converted to height) is extended and applied to polarimetric WSR-88D observations of six Northeast winter storms to survey their evolving, bulk vertical microphysical and kinematic structures. These analyses are supplemented using hourly analyses from the Rapid Refresh (RAP) model. Regions of ascent inferred from QVPs were consistently associated with notable polarimetric signatures, implying planar crystal growth when near −15°C, and riming and secondary ice production at higher temperatures. The heaviest snowfall occurred most often when ascent and enhanced propagation differential phase shift (
Abstract
The recent Weather Surveillance Radar-1988 Doppler (WSR-88D) network upgrade to dual-polarization capabilities allows for bulk characterization of microphysical processes in northeastern U.S. winter storms for the first time. In this study, the quasi-vertical profile (QVP) technique (wherein data from a given elevation angle scan are azimuthally averaged and the range coordinate is converted to height) is extended and applied to polarimetric WSR-88D observations of six Northeast winter storms to survey their evolving, bulk vertical microphysical and kinematic structures. These analyses are supplemented using hourly analyses from the Rapid Refresh (RAP) model. Regions of ascent inferred from QVPs were consistently associated with notable polarimetric signatures, implying planar crystal growth when near −15°C, and riming and secondary ice production at higher temperatures. The heaviest snowfall occurred most often when ascent and enhanced propagation differential phase shift (
Abstract
Storms that produce gargantuan hail (defined here as ≥6 in. or 15 cm in maximum dimension), although seemingly rare, can cause extensive damage to property and infrastructure, and cause injury or even death to humans and animals. Currently, we are limited in our ability to accurately predict gargantuan hail and detect gargantuan hail on radar. In this study, we analyze the environmental and radar characteristics of gargantuan hail–producing storms to define the parameter space of environments in which gargantuan hail occurs, and compare environmental parameters and radar signatures in these storms to storms producing other sizes of hail. We find that traditionally used environmental parameters used for severe storm prediction, such as most unstable convective available potential energy (MUCAPE) and 0–6-km vertical wind shear, display considerable overlap between gargantuan hail–producing storm environments and those that produce smaller hail. There is a slight tendency for larger MUCAPE values for gargantuan hail cases, however. Additionally, gargantuan hail–producing storms seem to have larger low-level storm-relative winds and larger updraft widths than those storms producing smaller hail, implying updrafts less diluted by entrainment and perhaps maximizing the liquid water content available for hail growth. Moreover, radar reflectivity or products derived from it are not different from cases of smaller hail sizes. However, inferred mesocyclonic rotational velocities within the hail growth region of storms that produce gargantuan hail are significantly stronger than the rotational velocities found for smaller hail categories.
Abstract
Storms that produce gargantuan hail (defined here as ≥6 in. or 15 cm in maximum dimension), although seemingly rare, can cause extensive damage to property and infrastructure, and cause injury or even death to humans and animals. Currently, we are limited in our ability to accurately predict gargantuan hail and detect gargantuan hail on radar. In this study, we analyze the environmental and radar characteristics of gargantuan hail–producing storms to define the parameter space of environments in which gargantuan hail occurs, and compare environmental parameters and radar signatures in these storms to storms producing other sizes of hail. We find that traditionally used environmental parameters used for severe storm prediction, such as most unstable convective available potential energy (MUCAPE) and 0–6-km vertical wind shear, display considerable overlap between gargantuan hail–producing storm environments and those that produce smaller hail. There is a slight tendency for larger MUCAPE values for gargantuan hail cases, however. Additionally, gargantuan hail–producing storms seem to have larger low-level storm-relative winds and larger updraft widths than those storms producing smaller hail, implying updrafts less diluted by entrainment and perhaps maximizing the liquid water content available for hail growth. Moreover, radar reflectivity or products derived from it are not different from cases of smaller hail sizes. However, inferred mesocyclonic rotational velocities within the hail growth region of storms that produce gargantuan hail are significantly stronger than the rotational velocities found for smaller hail categories.
Abstract
Recent studies document a polarimetric radar signature of refreezing. The signature is characterized by a low-level enhancement in differential reflectivity Z DR and a decrease in the copolar correlation coefficient ρ hv within a region of decreasing radar reflectivity factor at horizontal polarization Z H toward the ground, called the refreezing layer (RFL). The evolution of the signature is examined during three winter storms in which the surface precipitation-type transitions from ice pellets to freezing rain. A modified quasi-vertical profile (QVP) technique is developed, which creates inverse-distance-weighted profiles using all available polarimetric data within a specified range from the radar location. Using this new technique reveals that the RFL descends in time prior to the transition from ice pellets to freezing rain and intersects the ground at the approximate transition time. Transition times are estimated using both crowdsourced and automated precipitation-type reports within a specified domain around the radar. These radar-estimated transition times are compared to a recently developed precipitation-classification algorithm based on Rapid Refresh (RAP) model wet-bulb temperature T w profiles to explore potential benefits of analyzing QVPs during transition events. The descent of the RFL in the cases analyzed herein is related to low-level warm-air advection (WAA). A simple method for forecasting the transition time using QVPs is presented for cases of constant WAA. The repeatability of the refreezing signature’s descent in ice pellet to freezing rain transition events suggests the potential for its use in operational settings to create or modify short-term forecasts.
Abstract
Recent studies document a polarimetric radar signature of refreezing. The signature is characterized by a low-level enhancement in differential reflectivity Z DR and a decrease in the copolar correlation coefficient ρ hv within a region of decreasing radar reflectivity factor at horizontal polarization Z H toward the ground, called the refreezing layer (RFL). The evolution of the signature is examined during three winter storms in which the surface precipitation-type transitions from ice pellets to freezing rain. A modified quasi-vertical profile (QVP) technique is developed, which creates inverse-distance-weighted profiles using all available polarimetric data within a specified range from the radar location. Using this new technique reveals that the RFL descends in time prior to the transition from ice pellets to freezing rain and intersects the ground at the approximate transition time. Transition times are estimated using both crowdsourced and automated precipitation-type reports within a specified domain around the radar. These radar-estimated transition times are compared to a recently developed precipitation-classification algorithm based on Rapid Refresh (RAP) model wet-bulb temperature T w profiles to explore potential benefits of analyzing QVPs during transition events. The descent of the RFL in the cases analyzed herein is related to low-level warm-air advection (WAA). A simple method for forecasting the transition time using QVPs is presented for cases of constant WAA. The repeatability of the refreezing signature’s descent in ice pellet to freezing rain transition events suggests the potential for its use in operational settings to create or modify short-term forecasts.
ABSTRACT
Lightning flashes during snowstorms occur infrequently compared to warm-season convection. The rarity of such thundersnow events poses an additional hazard because the lightning is unexpected. Because cloud electrification in thundersnow storms leads to relatively few lightning discharges, studying thundersnow events may offer insights into mechanisms for charging and possible thresholds required for lightning discharges. Observations of four northern Colorado thundersnow events that occurred during the 2012/13 winter are presented. Four thundersnow events in one season strongly disagrees with previous climatologies that used surface reports, implying thundersnow may be more common than previously thought. Total lightning information from the Colorado Lightning Mapping Array and data from conterminous United States lightning detection networks are examined to investigate the snowstorms’ electrical properties and to compare them to typical warm-season thunderstorms. Data from polarimetric WSR-88Ds near Denver, Colorado, and Cheyenne, Wyoming, are used to reveal the storms’ microphysical structure and determine operationally relevant signatures related to storm electrification. Most lightning occurred within convective cells containing graupel and pristine ice. However, one flash occurred in a stratiform snowband, apparently triggered by a tower. Depolarization streaks were observed in the radar data prior to the flash, indicating electric fields strong enough to orient pristine ice crystals. Direct comparisons of similar lightning- and nonlightning-producing convective cells reveal that though both cells likely produced graupel, the lightning-producing cell had larger values of specific differential phase 
ABSTRACT
Lightning flashes during snowstorms occur infrequently compared to warm-season convection. The rarity of such thundersnow events poses an additional hazard because the lightning is unexpected. Because cloud electrification in thundersnow storms leads to relatively few lightning discharges, studying thundersnow events may offer insights into mechanisms for charging and possible thresholds required for lightning discharges. Observations of four northern Colorado thundersnow events that occurred during the 2012/13 winter are presented. Four thundersnow events in one season strongly disagrees with previous climatologies that used surface reports, implying thundersnow may be more common than previously thought. Total lightning information from the Colorado Lightning Mapping Array and data from conterminous United States lightning detection networks are examined to investigate the snowstorms’ electrical properties and to compare them to typical warm-season thunderstorms. Data from polarimetric WSR-88Ds near Denver, Colorado, and Cheyenne, Wyoming, are used to reveal the storms’ microphysical structure and determine operationally relevant signatures related to storm electrification. Most lightning occurred within convective cells containing graupel and pristine ice. However, one flash occurred in a stratiform snowband, apparently triggered by a tower. Depolarization streaks were observed in the radar data prior to the flash, indicating electric fields strong enough to orient pristine ice crystals. Direct comparisons of similar lightning- and nonlightning-producing convective cells reveal that though both cells likely produced graupel, the lightning-producing cell had larger values of specific differential phase
Abstract
Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero Z DR and high Z HH. In addition, a shallow region of very high Z DR is found consistently on the southern edge of the FFD, called the Z DR “arc.” The Z DR and K DP columns and midlevel “rings” of enhanced Z DR and depressed ρ HV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.
Abstract
Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero Z DR and high Z HH. In addition, a shallow region of very high Z DR is found consistently on the southern edge of the FFD, called the Z DR “arc.” The Z DR and K DP columns and midlevel “rings” of enhanced Z DR and depressed ρ HV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.
Abstract
Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (<10 mm h−1). The modeling results indicate that the amount of evaporation that occurs in the subcloud layer is strongly dependent on the initial shape of the drop size distribution aloft, which can be assessed with polarimetric measurements. Understanding how radar-estimated rainfall rates may change in height due to evaporation is important for quantitative precipitation estimates, especially in regions far from the radar or in regions of complex terrain where low levels may not be adequately sampled. In addition to quantifying the effects of evaporation, a simple method of estimating the amount of evaporation that occurs in a given environment based on polarimetric radar measurements of the reflectivity factor ZH and differential reflectivity Z DR aloft is offered. Such a technique may be useful to operational meteorologists and hydrologists in estimating the amount of precipitation reaching the surface, especially in regions of poor low-level radar coverage such as mountainous regions or locations at large distances from the radar.
Abstract
Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (<10 mm h−1). The modeling results indicate that the amount of evaporation that occurs in the subcloud layer is strongly dependent on the initial shape of the drop size distribution aloft, which can be assessed with polarimetric measurements. Understanding how radar-estimated rainfall rates may change in height due to evaporation is important for quantitative precipitation estimates, especially in regions far from the radar or in regions of complex terrain where low levels may not be adequately sampled. In addition to quantifying the effects of evaporation, a simple method of estimating the amount of evaporation that occurs in a given environment based on polarimetric radar measurements of the reflectivity factor ZH and differential reflectivity Z DR aloft is offered. Such a technique may be useful to operational meteorologists and hydrologists in estimating the amount of precipitation reaching the surface, especially in regions of poor low-level radar coverage such as mountainous regions or locations at large distances from the radar.
Abstract
Differential sedimentation of precipitation occurs because heavier hydrometeors fall faster than lighter ones. Updrafts and vertical wind shear can maintain this otherwise transient size sorting, resulting in prolonged regions of ongoing particle sorting in storms. This study quantifies the impact of size sorting on the S-band polarimetric radar variables (radar reflectivity factor at horizontal polarization ZH , differential reflectivity Z DR, specific differential phase K DP, and the copolar cross-correlation coefficient ρ hv). These variables are calculated from output of two idealized bin models: a one-dimensional model of pure raindrop fallout and a two-dimensional rain shaft encountering vertical wind shear. Additionally, errors in the radar variables as simulated by single-, double-, and triple-moment bulk microphysics parameterizations are quantified for the same size sorting scenarios.
Size sorting produces regions of sparsely concentrated large drops with a lack of smaller drops, causing Z DR enhancements as large as 1 dB in areas of decreased ZH , often along a ZH gradient. Such areas of enhanced Z DR are offset from those of high ZH and K DP. Illustrative examples of polarimetric radar observations in a variety of precipitation regimes demonstrate the widespread occurrence of size sorting and are consistent with the bin model simulations. Single-moment schemes are incapable of size sorting, leading to large underestimations in Z DR (>2 dB) compared to the bin model solution. Double-moment schemes with a fixed spectral shape parameter produce excessive size sorting by incorrectly increasing the number of large raindrops, overestimating Z DR by 2–3 dB. Three-moment schemes with variable shape parameters better capture the narrowing drop size distribution resulting from size sorting but can underestimate Z DR and overestimate K DP by as much as 20%. Implications for polarimetric radar data assimilation into storm-scale numerical weather prediction models are discussed.
Abstract
Differential sedimentation of precipitation occurs because heavier hydrometeors fall faster than lighter ones. Updrafts and vertical wind shear can maintain this otherwise transient size sorting, resulting in prolonged regions of ongoing particle sorting in storms. This study quantifies the impact of size sorting on the S-band polarimetric radar variables (radar reflectivity factor at horizontal polarization ZH , differential reflectivity Z DR, specific differential phase K DP, and the copolar cross-correlation coefficient ρ hv). These variables are calculated from output of two idealized bin models: a one-dimensional model of pure raindrop fallout and a two-dimensional rain shaft encountering vertical wind shear. Additionally, errors in the radar variables as simulated by single-, double-, and triple-moment bulk microphysics parameterizations are quantified for the same size sorting scenarios.
Size sorting produces regions of sparsely concentrated large drops with a lack of smaller drops, causing Z DR enhancements as large as 1 dB in areas of decreased ZH , often along a ZH gradient. Such areas of enhanced Z DR are offset from those of high ZH and K DP. Illustrative examples of polarimetric radar observations in a variety of precipitation regimes demonstrate the widespread occurrence of size sorting and are consistent with the bin model simulations. Single-moment schemes are incapable of size sorting, leading to large underestimations in Z DR (>2 dB) compared to the bin model solution. Double-moment schemes with a fixed spectral shape parameter produce excessive size sorting by incorrectly increasing the number of large raindrops, overestimating Z DR by 2–3 dB. Three-moment schemes with variable shape parameters better capture the narrowing drop size distribution resulting from size sorting but can underestimate Z DR and overestimate K DP by as much as 20%. Implications for polarimetric radar data assimilation into storm-scale numerical weather prediction models are discussed.
Abstract
The impact of the collisional warm-rain microphysical processes on the polarimetric radar variables is quantified using a coupled microphysics–electromagnetic scattering model. A one-dimensional bin-microphysical rain shaft model that resolves explicitly the evolution of the drop size distribution (DSD) under the influence of collisional coalescence and breakup, drop settling, and aerodynamic breakup is coupled with electromagnetic scattering calculations that simulate vertical profiles of the polarimetric radar variables: reflectivity factor at horizontal polarization Z H , differential reflectivity Z DR, and specific differential phase K DP. The polarimetric radar fingerprint of each individual microphysical process is quantified as a function of the shape of the initial DSD and for different values of nominal rainfall rate. Results indicate that individual microphysical processes (collisional processes, evaporation) display a distinctive signature and evolve within specific areas of Z H –Z DR and Z DR–K DP space. Furthermore, a comparison of the resulting simulated vertical profiles of the polarimetric variables with radar and disdrometer observations suggests that bin-microphysical parameterizations of drop breakup most frequently used are overly aggressive for the largest rainfall rates, resulting in very “tropical” DSDs heavily skewed toward smaller drops.
Abstract
The impact of the collisional warm-rain microphysical processes on the polarimetric radar variables is quantified using a coupled microphysics–electromagnetic scattering model. A one-dimensional bin-microphysical rain shaft model that resolves explicitly the evolution of the drop size distribution (DSD) under the influence of collisional coalescence and breakup, drop settling, and aerodynamic breakup is coupled with electromagnetic scattering calculations that simulate vertical profiles of the polarimetric radar variables: reflectivity factor at horizontal polarization Z H , differential reflectivity Z DR, and specific differential phase K DP. The polarimetric radar fingerprint of each individual microphysical process is quantified as a function of the shape of the initial DSD and for different values of nominal rainfall rate. Results indicate that individual microphysical processes (collisional processes, evaporation) display a distinctive signature and evolve within specific areas of Z H –Z DR and Z DR–K DP space. Furthermore, a comparison of the resulting simulated vertical profiles of the polarimetric variables with radar and disdrometer observations suggests that bin-microphysical parameterizations of drop breakup most frequently used are overly aggressive for the largest rainfall rates, resulting in very “tropical” DSDs heavily skewed toward smaller drops.
Abstract
The dual-polarization radar variables are especially sensitive to the microphysical processes of melting and size sorting of precipitation particles. In deep convective storms, polarimetric measurements of such processes can provide information about the airflow in and around the storm that may be used to elucidate storm behavior and evolution. Size sorting mechanisms include differential sedimentation, vertical transport, strong rotation, and wind shear. In particular, winds that veer with increasing height typical of supercell environments cause size sorting that is manifested as an enhancement of differential reflectivity (Z DR) along the right or inflow edge of the forward-flank downdraft precipitation echo, which has been called the Z DR arc signature. In some cases, this shear profile can be augmented by the storm inflow. It is argued that the magnitude of this enhancement is related to the low-level storm-relative environmental helicity (SRH) in the storm inflow.
To test this hypothesis, a simple numerical model is constructed that calculates trajectories for raindrops based on their individual sizes, which allows size sorting to occur. The modeling results indicate a strong positive correlation between the maximum Z DR in the arc signature and the low-level SRH, regardless of the initial drop size distribution aloft. Additional observational evidence in support of the conceptual model is presented. Potential changes in the Z DR arc signature as the supercell evolves and the low-level mesocyclone occludes are described.
Abstract
The dual-polarization radar variables are especially sensitive to the microphysical processes of melting and size sorting of precipitation particles. In deep convective storms, polarimetric measurements of such processes can provide information about the airflow in and around the storm that may be used to elucidate storm behavior and evolution. Size sorting mechanisms include differential sedimentation, vertical transport, strong rotation, and wind shear. In particular, winds that veer with increasing height typical of supercell environments cause size sorting that is manifested as an enhancement of differential reflectivity (Z DR) along the right or inflow edge of the forward-flank downdraft precipitation echo, which has been called the Z DR arc signature. In some cases, this shear profile can be augmented by the storm inflow. It is argued that the magnitude of this enhancement is related to the low-level storm-relative environmental helicity (SRH) in the storm inflow.
To test this hypothesis, a simple numerical model is constructed that calculates trajectories for raindrops based on their individual sizes, which allows size sorting to occur. The modeling results indicate a strong positive correlation between the maximum Z DR in the arc signature and the low-level SRH, regardless of the initial drop size distribution aloft. Additional observational evidence in support of the conceptual model is presented. Potential changes in the Z DR arc signature as the supercell evolves and the low-level mesocyclone occludes are described.
Abstract
The authors present observations of the microphysical characteristics of deep convection that overshoots the altitude of the extratropical tropopause from analysis of the polarimetric radar variables of radar reflectivity factor at horizontal polarization Z H, differential reflectivity Z DR, and specific differential phase K DP. Identified overshooting convective storms are separated by their organization and intensity into three classifications: organized convection, discrete ordinary convection, and discrete supercell convection. Composite analysis of identified storms for each classification reveals microphysical features similar to those found in previous studies of deep convection, with deep columns of highly positive Z DR and K DP representing lofting of liquid hydrometeors within the convective updraft and above the melting level. In addition, organized and discrete supercell classifications show distinct near-zero Z DR minima aligned horizontally with and at altitudes higher than the updraft column features, likely indicative of the frequent presence of large hail in each case. Composites for organized convective systems show a similar Z DR minimum throughout the portion of the convective core that is overshooting the tropopause, corresponding to Z H in the range of 15–30 dBZ and negative K DP observations, in agreement with the scattering properties of small hail and/or lump or conical graupel. Additional analyses of the evolution of overshooting storms reveals that the Z DR minima indicative of hail in the middle and upper troposphere and graupel in the overshooting top are associated with the mature and decaying stages of overshooting, respectively, supporting their inferred contributions to the observed polarimetric fields.
Abstract
The authors present observations of the microphysical characteristics of deep convection that overshoots the altitude of the extratropical tropopause from analysis of the polarimetric radar variables of radar reflectivity factor at horizontal polarization Z H, differential reflectivity Z DR, and specific differential phase K DP. Identified overshooting convective storms are separated by their organization and intensity into three classifications: organized convection, discrete ordinary convection, and discrete supercell convection. Composite analysis of identified storms for each classification reveals microphysical features similar to those found in previous studies of deep convection, with deep columns of highly positive Z DR and K DP representing lofting of liquid hydrometeors within the convective updraft and above the melting level. In addition, organized and discrete supercell classifications show distinct near-zero Z DR minima aligned horizontally with and at altitudes higher than the updraft column features, likely indicative of the frequent presence of large hail in each case. Composites for organized convective systems show a similar Z DR minimum throughout the portion of the convective core that is overshooting the tropopause, corresponding to Z H in the range of 15–30 dBZ and negative K DP observations, in agreement with the scattering properties of small hail and/or lump or conical graupel. Additional analyses of the evolution of overshooting storms reveals that the Z DR minima indicative of hail in the middle and upper troposphere and graupel in the overshooting top are associated with the mature and decaying stages of overshooting, respectively, supporting their inferred contributions to the observed polarimetric fields.
